fund_economics_computeComputes venture fund economics from a set of inputs (committed capital, fees, deployment, carry tiers): returns capital calls, fees, NAV, and gross/net returns. Free — any valid Hemrock API key works. Pass an "inputs" object.
| Name | Required | Description | Default |
|---|---|---|---|
| inputs | Yes | Fund inputs: committed capital, fees, portfolio construction, carry tiers. See list_concepts and the Fund Economics template for fields. |
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and openWorldHint, so the description is not burdened with safety traits. It adds useful context by specifying the outputs (capital calls, fees, NAV, returns) and that any valid API key works, which is an access/auth detail beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action, and contains no redundant or tangential information. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a compute tool with no output schema, the description lists both inputs and outputs, which covers the essential information. It also points to list_concepts and the Fund Economics template for field details, making it complete enough for an agent to proceed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the only parameter, so the baseline is 3. The description adds marginal value by naming 'deployment' (not explicitly in the schema) and instructing to 'Pass an inputs object', but largely mirrors the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Computes' with the resource 'venture fund economics' and enumerates both inputs (committed capital, fees, deployment, carry tiers) and outputs (capital calls, fees, NAV, gross/net returns). This clearly distinguishes it from sibling tools like cap_table_compute and exit_waterfall_compute.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied by the input/output list, but no explicit guidance is given on when to choose this tool over alternatives. The 'Free' statement is an access note, not a usage scenario. There are no exclusions or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool has a distinct purpose: three compute tools for different financial models, two list tools for discovery, and several get_* tools for retrieving context, concepts, prompts, checks, and access info. The get_* tools are numerous but their descriptions clearly differentiate them.
Naming convention is mixed: compute tools use noun_verb (cap_table_compute, exit_waterfall_compute), while access tools use verb_noun (get_access, list_models). This is still readable and somewhat predictable, but not uniform.
11 tools is well within the typical 3-15 range and appropriate for the server's purpose of financial modeling, covering both computation and supporting documentation/discovery without excess.
The compute tools cover the core cap table, exit waterfall, and fund economics models, and the supporting tools provide extensive educational and validation resources. However, list_models suggests more model engines may exist, but only three compute tools are exposed, leaving minor gaps.